Abstract Background Efficient and accurate delineation of organs at risk (OARs) is a critical procedure for treatment planning and dose evaluation. Deep learning‐based auto‐segmentation of OARs has shown promising results and is increasingly being used in radiation therapy. However, existing deep learning‐based auto‐segmentation approaches face two challenges in clinical practice: generalizability and human‐AI interaction. A generalizable and promptable auto‐segmentation model, which segments OARs of multiple disease sites simultaneously and supports on‐the‐fly human‐AI interaction, can significantly enhance the efficiency of radiation therapy treatment planning. Purpose Meta's segment anything model (SAM) was proposed as a generalizable and promptable model for next‐generation natural image segmentation. We further evaluated the performance of SAM in radiotherapy segmentation. Methods Computed tomography (CT) images of clinical cases from four disease sites at our institute were collected: prostate, lung, gastrointestinal, and head & neck. For each case, we selected the OARs important in radiotherapy treatment planning. We then compared both the Dice coefficients and Jaccard indices derived from three distinct methods: manual delineation (ground truth), automatic segmentation using SAM's ’segment anything’ mode, and automatic segmentation using SAM's ‘box prompt’ mode that implements manual interaction via live prompts during segmentation. Results Our results indicate that SAM's segment anything mode can achieve clinically acceptable segmentation results in most OARs with Dice scores higher than 0.7. SAM's box prompt mode further improves Dice scores by 0.1∼0.5. Similar results were observed for Jaccard indices. The results show that SAM performs better for prostate and lung, but worse for gastrointestinal and head & neck. When considering the size of organs and the distinctiveness of their boundaries, SAM shows better performance for large organs with distinct boundaries, such as lung and liver, and worse for smaller organs with less distinct boundaries, like parotid and cochlea. Conclusions Our results demonstrate SAM's robust generalizability with consistent accuracy in automatic segmentation for radiotherapy. Furthermore, the advanced box‐prompt method enables the users to augment auto‐segmentation interactively and dynamically, leading to patient‐specific auto‐segmentation in radiation therapy. SAM's generalizability across different disease sites and different modalities makes it feasible to develop a generic auto‐segmentation model in radiotherapy.
Extrachromosomal DNA Couples with ATM-mediated DNA Damage Response for Genome Instability in Tumors
Abstract Extrachromosomal DNA (ecDNA) drives the evolution of cancer cells by conferring survival advantages over normal cells. However, the functional importance of ecDNA replication and maintenance is yet to be evaluated, and the molecular components that contributed to these processes remain largely unknown. Here, using CRISPR-C (circularization of genes and chromosomes by CRISPR) technology and synthetic circular DNA mimicking ecDNA identified in tumors, we generated ecDNA-positive (ecDNA+) cell models. Using these models, we identified the proteins involved in ecDNA replication and maintenance and found DNA damage response (DDR)-related pathways were significantly enriched. We further demonstrated that ecDNA replication led to increased DDR and genome instability and DDR was also essential for ecDNA maintenance, consistent with observations that ecDNA+ tumors exhibited higher DDR scores than ecDNA-negative (ecDNA–) tumors in patients. ATM, MDC1, and CHK2, but not ATR, were activated in ecDNA+ cells compared to ecDNA– cells. Moreover, ecDNA+ cells were more sensitive to ATM and CHK2 inhibition. We further found that type II topoisomerase TOP2B and DNA ligase III (LIG3) were critical regulators for ecDNA replication and maintenance and related DDR. In summary, our findings of the reciprocal interactions between ecDNA and DDR provide new insights into detection and therapy for ecDNA+ tumors.
Real-world biomarker testing patterns among patients with metastatic colorectal cancer (mCRC) treated with later lines of therapy (LOT) in the United States (US) community oncology setting.
163 Background: Testing for BRAF and KRAS/NRAS mutations, HER2 amplifications, and MSI/MMR status is a standard of care for all patients with mCRC. There are limited real-world (RW) data regarding biomarker testing patterns among robust patients who are candidates for multiple LOT. We evaluated biomarker testing patterns among patients treated in community oncology practices who initiated regorafenib (REGO) and/or trifluridine/tipiracil (FTD/TPI), predominantly in 3rd or later lines of therapy. Methods: A retrospective analysis utilizing electronic medical record data from The US Oncology Network examined adult patients with mCRC who initiated REGO and/or FTD/TPI between 09/01/2015 and 11/30/2022 with follow-up until 05/31/2023. The proportion of patients tested for various biomarkers was assessed. Results: A total of 2684 mCRC patients initiated REGO and/or FTD/TPI (including 895 pts receiving both) in any LOT during the study period. The mean age of patients at baseline was 62.9 years, of whom 54.9% were male, 1599 (59.6%) patients were White and 436 (16.2%) were underrepresented minorities (Black or Hispanic/Latino). Patients were most commonly tested for KRAS mutations (75.2%) and least commonly for HER2 amplifications (22.6%). Age, gender, and race/ethnicity characteristics were similar between treatment subgroups, with 29.6% of minority and 23.1% of white patients not undergoing KRAS testing. Types of biomarkers tested and proportion of patients tested are reported in the table below. Conclusions: About one quarter of patients who were sufficiently robust to receive aggressive therapy did not undergo testing for KRAS, the oldest standard of care biomarker in CRC. We observed disparities by race/ethnicity. We also observed a correlation between rates of testing and treatment intensity, with patients who received both REGO and FTD/TPI having a higher rate of testing than those who received only one of the treatments. Understanding the pitfalls in biomarker testing will help pave the way for appropriate and equitable access to cancer care. [Table: see text]
The Lymphoma Epidemiology of Outcomes cohort study: Design, baseline characteristics, and early outcomes
AbstractTo address the current and long‐term unmet health needs of the growing population of non‐Hodgkin lymphoma (NHL) patients, we established the Lymphoma Epidemiology of Outcomes (LEO) cohort study (NCT02736357; https://leocohort.org/). A total of 7735 newly diagnosed patients aged 18 years and older with NHL were prospectively enrolled from 7/1/2015 to 5/31/2020 at 8 academic centers in the United States. The median age at diagnosis was 62 years (range, 18–99). Participants came from 49 US states and included 538 Black/African‐Americans (AA), 822 Hispanics (regardless of race), 3386 women, 716 age <40 years, and 1513 rural residents. At study baseline, we abstracted clinical, pathology, and treatment data; banked serum/plasma (N = 5883, 76.0%) and germline DNA (N = 5465, 70.7%); constructed tissue microarrays for four major NHL subtypes (N = 1189); and collected quality of life (N = 5281, 68.3%) and epidemiologic risk factor (N = 4489, 58.0%) data. Through August 2022, there were 1492 deaths. Compared to population‐based SEER data (2015–2019), LEO participants had a similar distribution of gender, AA race, Hispanic ethnicity, and NHL subtype, while LEO was underrepresented for patients who were Asian and aged 80 years and above. Observed overall survival rates for LEO at 1 and 2 years were similar to population‐based SEER rates for indolent B‐cell (follicular and marginal zone) and T‐cell lymphomas, but were 10%–15% higher than SEER rates for aggressive B‐cell subtypes (diffuse large B‐cell and mantle cell). The LEO cohort is a robust and comprehensive national resource to address the role of clinical, tumor, host genetic, epidemiologic, and other biologic factors in NHL prognosis and survivorship.
Racial and ethnic disparities in untreated patients with hepatitis C virus‐related hepatocellular carcinoma but not in those with sustained virologic response
SummaryBackgroundRacial and ethnic disparities exist for hepatitis C virus (HCV) treatment and hepatocellular carcinoma (HCC) survival.AimTo evaluate the impact of HCV treatment on such disparities.MethodsIn a retrospective cohort study, we analysed 6069 patients with HCV‐related HCC (54.2% Asian, 30.1% White, 8.5% Black, and 7.3% Hispanic) from centres in the United States and Asia.ResultsThe mean age was 61, 60, 59 and 68, respectively, for White, Black, Hispanic and Asian patients. Black patients were most likely to have Barcelona Clinic Liver Cancer stage D, vascular invasion and distant metastasis (23% vs. 5%–15%, 20% vs. 10%–17% and 10% vs. 5%–7%, respectively; all p < 0.0001). Treatment rate with direct‐acting antiviral agents (DAA) was 35.9% for Asian, 34.9% for White, 30.3% for Hispanic (30.3%), and 18.7% for Black patients (p < 0.0001). Among those untreated or without sustained virologic response (SVR), 10‐year survival rates were 35.4, 27.5, 19.3 and 14.0, respectively, for Asian, Hispanic, White and Black patients (p < 0.0001). There were no statistically significant differences among those with SVR (p = 0.44). On multivariable analysis adjusted for relevant confounders, there was no statistically significant association between survival and being Hispanic (aHR: 0.68, p = 0.26) or Black (aHR: 1.18, p = 0.60) versus White. There was a significant association between being Asian American and survival (aHR: 0.24, p = 0.001; non‐U.S. Asian: aHR: 0.66, p = 0.05), and for SVR (aHR: 0.30, p < 0.0001).ConclusionDAA treatment rates were suboptimal. Racial and ethnic disparities resolved with HCV cure. Early diagnosis and improved access to HCV treatment is needed for all patients with HCV infection.
Abstract Microglia, the major resident immune cells in the central nervous system, serve as the frontline soldiers against cerebral ischemic injuries, possibly along with metabolic alterations. However, signaling pathways involved in the regulation of microglial immunometabolism in ischemic stroke remain to be further elucidated. In this study, using single‐nuclei RNA sequencing, a microglial subcluster up‐regulated in ischemic brain tissues is identified, with high expression of Igf1 and Trem2, neuroprotective transcriptional signature and enhanced oxidative phosphorylation. Microglial depletion by PLX3397 exacerbates ischemic brain damage, which is reversed by repopulating the microglia with high Igf1 and Trem2 phenotype. Mechanistically, Igf1 serves as one of the major down‐stream molecules of Trem2, and Trem2‐Igf1 signaling axis regulates microglial functional and metabolic profiles, exerting neuroprotective effects on ischemic stroke. Overexpression of Igf1 and supplementation of cyclocreatine restore microglial glucometabolic levels and cellular functions even in the absence of Trem2. These findings suggest that Trem2‐Igf1 signaling axis reprograms microglial immunometabolic profiles and shifts microglia toward a neuroprotective phenotype, which has promising therapeutic potential in treating ischemic stroke.
Abstract 17014: Differences in the Outcomes of Catheter Ablation for Ventricular Tachycardia in Patients With Ischemic versus Non-Ischemic Cardiomyopathy
Background: Catheter ablation is an effective tool to reduce ventricular tachycardia (VT) burden. There is a lack of robust data studying the characteristics and outcomes of VT ablation in patients with ischemic (ICM) versus non-ischemic cardiomyopathy (NICM). Aims: The aim of this study was to assess the impact of ICM vs NICM on outcomes of VT ablation. Methods: A single-center, retrospective study of patients undergoing catheter ablation for VT was conducted. Results: A total of 168 patients, undergoing 200 VT ablation procedures, were included in this study. NICM group (112 procedures) was compared to ICM group (88 procedures). Patients in the ICM group were older (66.6 ± 13.4 vs 58.9 ± 14.4 years) and had higher rates of prior myocardial infarction (65.9% vs 3.6) and coronary artery bypass graft surgery (40.9% vs 1.8%). Overall, ICM group had more comorbidities like hypertension (80.7% vs 52.7%), diabetes mellitus (23.9% vs 12.5%), chronic kidney disease (45.5% vs 35.7%), stroke (17% vs 7.1%), and lower left ventricular ejection fraction (36.8 ± 13.2% vs 43.1 ± 14.7%). The ICM group had lower incidence of prior cardiac valvular surgery (9.1% vs 29.5%). The inducibility of VT (93% vs 93.5%; p= 1.0) and the number of different VT morphologies induced during the case (1.9 ± 1.5 vs 2.3 ± 2.5; p=0.19) was similar between the two groups. There was no acute mortality in either group. There was a non-significant trend towards greater VT recurrence in the NICM group (43.2% vs 33.3%, p= 0.19). However, patients with NICM had a lower VT-free survival as determined by Kaplan-Meier analysis (p=0.05) [Figure]. Long term mortality was higher in ICM group when compared to NICM group (18.2% vs 8.9%, p<0.01). Conclusion: Patients undergoing VT ablation in the NICM group when compared to the ICM group were noted to be younger, had fewer comorbidities, and lower long-term mortality. However, they had significantly less VT-free survival, likely owing to more challenging substrate responsible for VT.
Abstract 15352: Deep Learning Model-Enabled Electrocardiogram to Localize Premature Ventricular Contractions in Patients Referred for Catheter Ablation
Introduction: Accurate pre-procedure localization of the premature ventricular contractions (PVCs) is critical in preparing for the ablation. So far, no tools exist for artificial intelligence guided PVC-localization. Hypothesis: Trained deep learning model will be able to predict the site of origin (SOO) of PVCs using 12 lead electrocardiogram (ECG). Methods: We analyzed 707 ECG-ablation pairs from 2403 patients who had at least one ECG flagged for PVCs in the 6 months prior to their procedure. First, we used a cohort of 100,000 ECGs without PVCs and 10,000 ECGs with PVCs to train a convolutional neural network (CNN) to isolate the ECG segments with PVCs in them from a 12-lead ECG (Figure 1). We then trained two models, one utilizing a 10-second 12-lead ECG, and the other with just the isolated PVC beats as input. The models were trained using the Keras framework with TensorFlow (Google). Results: The mean age of the patients in the cohort was 61.2 ± 15.0 years. 66.3 percent of patients underwent left ventricle ablation, 54.6 percent had outflow ablation, and 55.3 percent had ablation of sites with leftward axis (septal location for midline and left ventricle PVCs). The model trained on 10-second ECGs yielded validation and test AUCs of 0.941 and 0.931 for outflow, 0.898 and 0.891 for ventricle, and 0.863 and 0.846 for leftward axis (Figure 1A). The model trained on isolated segments containing PVC beats yielded validation and test AUCs of 0.966 and 0.957 for outflow, 0.879 and 0.907 for ventricle, and 0.846 and 0.829 for SOO for leftward axis (Figure 1B). Conclusions: We have trained an accurate convolutional neural network that can predict SOO using the surface ECG. Further fine-tuning would be needed to refine the model and develop prediction of specific sites.
Learning Physician’s Treatment for Alzheimer's Disease based on Electronic Health Records and Reinforcement Learning
2023 IEEE 11th International Conference on Healthcare Informatics (ICHI) | December 11, 2023 | Volume: No volume available | Issue: No issue available | Pages: 525-526
Introduction: PET/CT is the standard-of-care for staging and therapy response assessment in lymphoma. Fluorodeoxyglucose (FDG)-avidity in extranodal marginal zone lymphoma (EMZL) remains controversial with some variability by extranodal location. The current Lugano classification recommends the use of CT scans only in staging and follow-up for EMZL. However, emerging data from small studies have challenged this suggestion. In this study we aimed to determine the ability of PET/CT to detect FDG-avid EMZL during staging work-up. Methods: First, we retrospectively analyzed the University of Miami (UM) MZL database (period 2/2016-1/2023) searching for patients who underwent staging PET/CT. Images were reviewed by expert radiologists to ascertain avidity of tumor and not surrounding tissue, with specific attention to ocular and GI locations; if scans were not available (n=15), we retrieved data from reports (results presented in part at ICML2023). Next, we aimed to validate the initial UM results additionally analyzing data from imaging reports for patients prospectively enrolled in the Lymphoma Epidemiology of Outcomes (LEO) MZL cohort (period 7/2015-5/2020), excluding LEO patients from Miami to avoid overlap. Patients with high-grade transformation at diagnosis were excluded. For patients with >1 extranodal site, each location was counted independently. We considered FDG-avid disease if SUVmax was ≥2 as this value is commonly observed between mediastinal blood pool (BP) and liver background. To normalize data, we calculated ratios of lymphoma SUVmax versus both BP and liver background, as available. Patients without measurable disease were excluded from analysis. Results: Among 210 patients with EMZL in the UM cohort, 152 had staging PET/CT and were analyzed. Twenty-two patients demonstrated >1 extranodal site providing a total of 187 locations. The LEO cohort included 411 patients from 7 centers, with 235 having available imaging reports. Fifty-two patients in this cohort demonstrated >1 extranodal site providing a total of 306 locations. Disease distribution is depicted in Table 1. Among 187 EMZL locations in the UM cohort, the most common were gastric (n=33, 17.6%), ocular (n=31, 16.6%), lung (n=30, 16%), skin and soft tissue (n=16, 8.6%, each). Similarly, lung (n=63; 20.6%), soft tissue (n=46; 15%), gastric and ocular (n=34 each; 11%) were common locations in the LEO cohort. EMZL demonstrated FDG-avidity (SUVmax ≥2) across all locations with identical values in both cohorts (UM= 78.1% & LEO= 76.5%). FDG-avidity by location is shown in Table 1A & B with salivary gland (100% & 100%), lung (93.3% & 95.2%), soft tissue (93.8% & 100%), and airways (90.9% & 100%) demonstrating high avidity in both cohorts. Contrarily, skin was commonly non-FDG avid (93.8% & 81%). The median size of FDG-avid lesions was 2.4cm (range, 0.7-17.4) in UM and 2.9cm (range, 0.1-12) in LEO cohorts. In patients with >1 extranodal site FDG-avidity was nearly universal across sites (UM=93% & LEO=100%). We observed a significant correlation between lymphoma size and FDG-avidity for UM (r=0.33; P=0.001), and for LEO (r=0.55; P<0.0001). In patients with background FDG-avidity data in the UM cohort (n=150), a BP index and liver index ≥1 detected lymphoma in 79.3% & 71.5% cases, respectively. We were unable to calculate indexes in LEO cohort since only limited data on BP (n=26) and liver (n=19) background was available in imaging reports. Conclusions: This study represents the largest analysis evaluating accuracy of PET/CT to determine initial tumor burden in 387 patients with EMZL. We demonstrate that EMZL is largely an FDG-avid disease across two cohorts, and PET/CT should be included in the staging of these patients while acknowledging possible limited sensitivity in GI locations due to physiologic uptake. Furthermore, we observed that patients with multiple extranodal locations demonstrate uniform FDG-avidity across all sites except for skin involvement. Based on our results we recommend the incorporation of PET/CT into standard staging of EMZL in planned revised Lugano classification guidelines. In those demonstrating initial FDG-avidity, a lower SUVmax threshold of SUVmax ≥2, comparison to mediastinal BP rather than to liver background activity and evaluating for resolution of focal FDG-avidity should be considered to assess treatment response in routine care and clinical trials.